Web searching has become one of the most common and important activities on the Internet. Most of the time users enter their search queries (typically by using keywords such as a phrase or a combination of terms) into a search engine to look for the information they need. The search engine then examines the search query and provides a listing of best-matching web pages according to a given criterion or criteria. Traditional Information Retrieval (IR) technology used by search engines is typically based on the occurrence of words in documents. Some search engines provide certain advanced features such as the proximity search which allows users to define the distance between keywords. There is also concept-based searching where the research involves using statistical analysis on pages containing the words or phrases the user searches for. In addition, a semantic search attempts to augment and improve traditional search results (based on IR technology) by understanding user's intent and the contextual meaning of search terms, and using data from the semantic web, which defines and links the data on the web facilitating more efficient discovery and integration. Major web search engines like GOOGLE® and BING® have incorporated some Semantic Search elements.
However, a semantic search has only been applied to a very limited extent, not only because of the difficulty of creating a semantic web, but also due to difficulty in extracting and understanding a user's intent from the text of a search query, which involves natural language processing and a semantic dictionary etc.
Most currently used search engines and search portals (whether semantic search engines or not) present users with a Graphic User Interface (GUI) with a search box which allows users to enter free form queries. The advantage of a search box is, for instance, that it is very easy and handy to use, however the disadvantage is that users are limited to specify their requests using words, phrases or simple sentences. According to Wikipedia, most users usually enter primitive search queries with an average length of 2.4 terms. Less than 5% of users would use advanced search features. Thus it may be difficult to find the relevant information based on a brief and implicit query.
Both searchers and content providers need a common and innovative form (such as a GUI) to enable searching with sufficient and specific details, thus increasing the chance of better matching results.
There is thus a need in the art for a new method and system for searching through a GUI.
References considered to be relevant as background to the presently disclosed subject matter are listed below. Acknowledgement of the references herein is not to be inferred as meaning that these are in any way relevant to the patentability of the presently disclosed subject matter.
U.S. Pat. No. 8,001,152 (Solan) issued on Aug. 16, 2011 discloses a search interface and searching technology for interactive search refinement based on feature similarity (ISRFS), which provides an interactive search tool based on human associative and semantic knowledge. Given a query, the tool may retrieve the most suitable textual items in a repository of textual data that is categorized or/and partially tagged. In the user interface, an equalizer controller may be used to refine the search results, for example, based on manually or automatically extracted features and a graded semantic scale to adjust the weights of the various features. The technology may be applied to any data repository.
WO 2011/159989 (Ghosh et al.) published on Dec. 22, 2011 discloses a new approach that contemplates systems and methods to generate customized subjective search results from the perspective of a user who conducts the search or any other subject entity chosen by the user. A scored subject list is created from the user's network of sources/subjects/contacts, where each element on the list is a subject/source and the score reflects the subject's potential influence or closeness of its connection/relation with the user. Once created, the subject list is then used as a bias filter on the list of citations from search results. With such influence-weighted citation scores, objects and/or subjects from citations of subjects that have a big influence on or enjoy high respect from the user, will be ranked prominently in the search result presented to the user, thus biasing the search results from the user's perspective.
US 2011307465 (Ghosh et al.) published on Dec. 15, 2011 discloses a new approach that contemplates systems and methods to ascribe or transfer metadata from one search-related entity to another, where each entity can be one of subject or source, citation, and object or target. First, one or more complete or incomplete attributes associated with one or more of entities across source, citation and target are identified with a high degree of probable accuracy, wherein such metadata or attributes include but are not limited to, time, language, and location of the entities. The identified attributes are then ascribed or transferred from one entity where the metadata is available to other search entities. Finally, the transferred attributes can be utilized to facilitate the selection and ranking of the cited targets for the search result.
WO 2005022402 (Gosse et al.) published on Mar. 10, 2005 discloses a method, device, and software for presenting search results obtained from a plurality of databases, based on an end-user specified query. In an embodiment, the search results are combined from results from a first index and results from a second index. The first index comprises a plurality of index entries modifiable by an administrator, and the second index comprises a plurality of index entries that are not modifiable by the administrator. In the combined search results, any search result from the second index for which an associated key field is identical to the associated key field of a matching search result in the first set of search results is discarded in favor of the matching search result in the first set of search results.
“Vi-Fi (Visible-Findable)—how to describe and to search sites with standard and universal semantic-pragmatic tree: Semantic Web as Pragmatic Web” (Alexander Zelitchenko) discloses a new approach to web search, which provides a powerful narrow-focused marketing tool for small on-line businesses as well as for anyone who wishes to increase visibility in the Web. The core of approach is an observable (small enough—of the order of tens) standard universal system of both attributes and their values, which describes requests of WEB-users and content (offers) of sites in the same language and allow to calculate easily congruency between query and site. This system is based on pragmatics (logic of customer's request) rather than on usual (“pure”) ontology and is organized as tree. Both web-masters and searchers browse this tree to describe their sites and queries respectively. The tree changes until taking its ultimate form, as approach is realized.